Wang Dongyang, Wu Xiaohong, Jiang Guanghui, Yang Jianye, Yu Zhanhui, Yang Yanbo, Yang Wenqian, Niu Xiaohui, Tang Ke, Gong Jing
Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, China.
Department of Biochemistry and Molecular Biology, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Front Oncol. 2022 Oct 18;12:1035855. doi: 10.3389/fonc.2022.1035855. eCollection 2022.
Genome-wide association study (GWAS) has identified thousands of single nucleotide polymorphisms (SNPs) associated with complex diseases and traits. However, deciphering the functions of these SNPs still faces challenges. Recent studies have shown that SNPs could alter chromatin accessibility and result in differences in tumor susceptibility between individuals. Therefore, systematically analyzing the effects of SNPs on chromatin accessibility could help decipher the functions of SNPs, especially those in non-coding regions. Using data from The Cancer Genome Atlas (TCGA), chromatin accessibility quantitative trait locus (caQTL) analysis was conducted to estimate the associations between genetic variants and chromatin accessibility. We analyzed caQTLs in 23 human cancer types and identified 9,478 caQTLs in breast carcinoma (BRCA). In BRCA, these caQTLs tend to alter the binding affinity of transcription factors, and open chromatin regions regulated by these caQTLs are enriched in regulatory elements. By integrating with eQTL data, we identified 141 caQTLs showing a strong signal for colocalization with eQTLs. We also identified 173 caQTLs in genome-wide association studies (GWAS) loci and inferred several possible target genes of these caQTLs. By performing survival analysis, we found that ~10% caQTLs potentially influence the prognosis of patients. To facilitate access to relevant data, we developed a user-friendly data portal, BCaQTL (http://gong_lab.hzau.edu.cn/caqtl_database), for data searching and downloading. Our work may facilitate fine-map regulatory mechanisms underlying risk loci of cancer and discover the biomarkers or therapeutic targets for cancer prognosis. The BCaQTL database will be an important resource for genetic and epigenetic studies.
全基因组关联研究（GWAS）已鉴定出数千个与复杂疾病和性状相关的单核苷酸多态性（SNP）。然而，解读这些SNP的功能仍面临挑战。最近的研究表明，SNP可改变染色质可及性，并导致个体间肿瘤易感性的差异。因此，系统分析SNP对染色质可及性的影响有助于解读SNP的功能，尤其是非编码区的SNP。利用来自癌症基因组图谱（TCGA）的数据，进行了染色质可及性数量性状基因座（caQTL）分析，以估计基因变异与染色质可及性之间的关联。我们分析了23种人类癌症类型中的caQTL，并在乳腺癌（BRCA）中鉴定出9478个caQTL。在BRCA中，这些caQTL倾向于改变转录因子的结合亲和力，受这些caQTL调控的开放染色质区域富含调控元件。通过与表达数量性状基因座（eQTL）数据整合，我们鉴定出141个与eQTL共定位信号强烈的caQTL。我们还在全基因组关联研究（GWAS）位点中鉴定出173个caQTL，并推断出这些caQTL的几个可能的靶基因。通过进行生存分析，我们发现约10%的caQTL可能影响患者的预后。为便于获取相关数据，我们开发了一个用户友好的数据门户BCaQTL（http://gong_lab.hzau.edu.cn/caqtl_database），用于数据搜索和下载。我们的工作可能有助于精细绘制癌症风险位点潜在的调控机制，并发现癌症预后的生物标志物或治疗靶点。BCaQTL数据库将成为遗传和表观遗传研究的重要资源。
